Oct 21, 2008
WindPower 2.0: technology rises to the challenge
As wind turbines grow larger and reach more remote locations, they’ll need new technologies and systems to keep them running, says Peter Clive.
To a significant extent, wind power meets the need for a technology that provides a secure energy supply and helps limit the effects of anthropogenic global warming. While wind turbines are successful, the accelerating rate of installation of generating capacity is resulting in larger machines in greater numbers in progressively more remote, inaccessible and challenging locations than originally envisaged. For example, recent announcements on offshore wind power, if implemented, would expand UK wind power generating capacity by an order of magnitude . Currently, existing wind turbine designs are being scaled up to achieve the increased capacity required. But it is apparent that more fundamental adjustments are needed to create turbines tailored to these new environments and to achieve the increase in the power they are to generate .
Several features of this new generation of wind power are already evident. Here I’ll discuss three features that are just entering the scene:
• Turbine technology itself is changing to provide both greater power and better reliability
• Operation and maintenance strategies are becoming more intelligent to accommodate more demanding circumstances
• Remote sensing techniques are coming into use to characterize more fully the wind flow influencing the performance of the turbines
Winding up the turbines
Until now the increase in wind turbine power has generally been achieved by adapting existing designs. This approach has also been adopted to adapt machines for use in marine environments and make them more robust. But it’s no longer adequate to address today’s improvements so more fundamental solutions to the problems of increased capacity and reduced access for maintenance are under development. A number of wind turbine components are prone to failure and are difficult and expensive to repair or replace, for example bearings, inverters and gearboxes, giving rise to maintenance issues. As a result, direct drive machines that use permanent magnets rather than electromagnets in synchronous generators are now under construction. This eliminates the need for a gearbox. What’s more, the search for even better power-to-weight ratios is leading to the development of direct drive generators that use superconducting magnets. The advent of high temperature superconductivity enhances the viability of these solutions - today’s superconductors can operate at temperatures of over 77K, the boiling point of nitrogen. Indeed it may be possible that cryogen-free pulsed refrigeration will play a role in future, and that other failure-prone components such as bearings are eliminated. That means we are likely to see machines whose rated capacity, in Megawatts, is in double figures within the next five years, provided the costs of the necessary high-temperature superconducting materials, such as YBCO (yttrium barium copper oxide) ribbon, decrease as anticipated.
The technology underlying the turbines themselves may change, but its full benefit will not be reaped unless operation and maintenance strategies are altered to reflect lack of access to increasingly remote locations. The management of strategic spares and key personnel suitable for responding to onshore events is not well matched to the requirements offshore, where the availability of weather windows may limit access. In general offshore it’s no longer sufficient to wait until a component fails before responding. This means more detailed monitoring of turbines and more intelligent processing of the information gathered. Individual components can undergo condition monitoring, which entails the installation of additional sensors to detect vibrations and other phenomena that enable deductions about the condition of specific components. However this may entail downtime during detector installation, and may have warranty implications as a result of potentially altering the hardware configuration of the turbine beyond the scope of the original warranty.
A complementary approach, which avoids these issues, is performance monitoring and optimization. Operational data is already routinely acquired by the turbines’ SCADA (supervisory control and data acquisition) systems. These data can be analyzed to provide an indication of turbine health on a regular basis. The performance of a turbine that’s operating normally varies as a result of changes in the prevailing conditions. Deviations from a normal response to these conditions that are detected through routine performance monitoring can alert operators to performance issues. Rapid and routine performance monitoring that enables operators to converge quickly on areas where their attention can most profitably be directed requires the development of innovative data visualization and analysis tools, such as those implemented in the sgurrtrend software suite . These identify deviations of a turbine’s response to varying conditions from the range corresponding to normal operation and correlate these deviations in performance with alarms and other event data recorded by the SCADA system.
The establishment of benchmarks for turbine performance is benefiting from the increasing extent of data aggregation in the industry. This involves bringing together routine operational SCADA data from turbines in multiple wind farms into a single data source. Currently performance monitoring is conducted using benchmarks that characterize multiple turbines’ varying response to prevailing conditions across a single wind farm or a single turbine’s varying response over time. In future it could be that data aggregation will enable performance monitoring of individual turbines to be conducted with reference to operational benchmarks established over entire fleets of turbines .
Wakes, turbulence, shear and veer
Using remote sensing and modeling tools at proposed wind turbine locations enables more accurate prediction of conditions prior to construction, as well as more optimal configuration of the turbines after construction. Once the performance and condition of the turbines is well known, it makes sense to acquire detailed information about the wind conditions impacting performance. This can be achieved using remote sensing technology known as LIDAR (light detection and ranging). LIDAR devices are compact, portable, discreet ground-based instruments that emit a laser beam (see figure). The Doppler shift of the light back-scattered by aerosols – microscopic airborne particulates moving with the wind – indicates wind velocity.
Currently control hardware regulates turbines using data acquired by nacelle-mounted wind-measurement kit only after the wind has already passed through the rotor. Remote sensing apparatus such as LIDAR allows the measurement of wind conditions before they affect turbine performance. That enables turbine control hardware to regulate the machines in order to alleviate the fatigue loading and sub-optimal performance that arise from anomalous wind shear, gusts, wind veer and turbulence.
LIDAR has already found a role prior to wind farm construction by allowing direct measurements to be made where wind flow was previously approximated using models. The validation and refinement of increasingly sophisticated non-linear computational fluid dynamics (CFD) models using direct LIDAR measurements is driving down uncertainty in energy yield prediction. In turn, this improves the financial prospects of projects under development.
The use of LIDAR in wind power applications is a rapidly developing field, as illustrated by the fact that the devices available have yet to converge on an optimal design. Recent developments will support greater confidence in LIDAR data acquired in the complex terrain typical of upland wind farms - this promises to extend the use of these devices further .
Offshore wind resource assessment currently requires the installation of cup anemometry (wind measurement) on expensive lattice towers mounted on offshore platforms. One particularly promising LIDAR development is the potential to radically reduce these costs by placing less stringent requirements on platform design and construction, and the possibility of combining the LIDAR data with both mesoscale climate models and synthetic aperture radar (SAR) data acquired from satellites . What’s more, developments in systems for compensating wave motion promise to eliminate the need for fixed platforms altogether.
Wind power is a relatively young industry characterized by rapid development to match ever- increasing demand. This is an exciting time to be involved and one when it is still possible to make fundamental contributions to the progress of the industry. New developments such as those discussed here are ushering in a new generation of wind power technology; with the advent of this WindPower2.0 the industry is achieving a new level of maturity that will bring widespread benefits.
 "Offshore wind: moving up a gear", BVG Associates, British Wind Energy Association, 2007
 UpWind project, EU 6th Framework Program (www.upwind.eu)
 "Making the most of SCADA data: wind farm performance monitoring", D. McLaughlin, J.H. McKenzie, P.J.M. Clive, 10th World Renewable Energy Congress, 2008
 "Understanding the utility of SCADA data in optimising wind farms performance", P.J.M. Clive, Wind Energy Update Newsletter, issue 1, 2008 (Wind Eenergy Update)
 "Mitigating the impact of complex terrain on LIDAR wind resource assessment accuracy", P.J.M. Clive, 30th Annual Conference of the British Wind Energy Association, 2008
 NORSEWInD project, EU 7th Framework Program (NORSEWInD)
About the author
Peter Clive is a Technical Development Consultant with SgurrEnergy, UK, which has given him many opportunities to participate in the rapidly developing wind power industry. His interests include the use of remote sensing instruments such as LIDAR, and the development of techniques for extracting useful turbine performance information from operational SCADA data. Peter's background is in physics, and he obtained his doctorate in nuclear physics from Glasgow University in 2002.